DBMS > Elasticsearch vs. IRONdb vs. JaguarDB

System Properties Comparison Elasticsearch vs. IRONdb vs. JaguarDB

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Search engine

Time Series DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	141.63
Rank	#8	Overall
	#1	Search engines

Score	0.37
Rank	#327	Overall
	#29	Time Series DBMS

Score	0.01
Rank	#396	Overall
	#64	Key-value stores

Website

www.elastic.co/elasticsearch

www.circonus.com/solutions/time-series-database

www.datajaguar.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.circonus.com/irondb

www.datajaguar.com/support.php

Developer

Elastic

Circonus LLC.

DataJaguar, Inc.

Initial release

2010

2017

2015

Current release

8.6, January 2023

V0.10.20, January 2018

2.9.4 September 2018

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

GPL V3.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (Circonus Analytics Query Language: CAQL)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP API

JDBC
ODBC

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

yes, in Lua

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

User concepts

Access control

rights management via user accounts

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Elastic Unveils the Elasticsearch Relevance Engine for Artificial ...
23 May 2023, Business Wire

Elastic democratizes generative AI for proprietary data with the ...
23 May 2023, KMWorld Magazine

Elasticsearch Relevance Engine brings new vectors to generative AI
23 May 2023, VentureBeat

Somehow Amazon's Open Source Fork of ElasticSearch Has ...
14 May 2023, Slashdot

Building A Log Analytics Solution 10 Times More Cost-Effective ...
15 May 2023, hackernoon.com

provided by Google News

On the Radar: COVID-19, Circonus, and Fake FB Accounts
4 March 2020, Datanami

provided by Google News

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